将unix时间戳转换为avro并将其存储在BigQuery中

问题描述：

Avro模式:

{
  "name": "Entity",
  "type": "record",
  "namespace": "com.foobar.entity",
  "fields": [
    {
      "name": "attribute",
      "type": "string"
    },
    {
      "name": "value",
      "type": "int"
    },
    {
      "name": "timestamp",
      "type": { "type": "long", "logicalType": "timestamp-micros" }
    }
  ]
}

源时间戳是Unix格式，精度为毫秒.

The source timestamp is in Unix format with milli second precision.

将此类记录放入BigQuery时，在BigQuery数据预览中会得到类似 1970-01-19 01:18:19.415 UTC 的值.但是我存储的值是 1559899418 ，它是星期五，2019年6月7日09:23:38 .有什么想法吗?

When I put such records into BigQuery I get values like 1970-01-19 01:18:19.415 UTC in the BigQuery data preview. However the value I stored is 1559899418 which is Friday, 7. June 2019 09:23:38. Any ideas why?

参考: https://cloud.google.com/bigquery/docs/loading-data-cloud-storage-avro#logical_types

答

您的时间戳偏离了1000倍.实际上， 1559899418 对应于星期五，7 June 2019 09:23:38 ，但这是秒精度( Unix时间戳)，而不是毫秒.而 1559899 (1559899418的千分之一)确实对应于 1970-01-19 01:18:19

Your timestamp is off by a factor 1000. Indeed, 1559899418 corresponds to Friday, 7. June 2019 09:23:38, but that's second-precision (Unix timestamp), not millisecond. And 1559899 (one thousandth of 1559899418) does indeed correspond to 1970-01-19 01:18:19

将unix时间戳转换为avro并将其存储在BigQuery中

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